Senior Manager, Data Engineering
$150,000–$200,000 year
On-siteMcKinney, Texas, United States
McKinney, Texas, United StatesOn-siteFull Time$150,000–$200,000 yearSenior LevelLarge
Full TimeSenior LevelLarge
Job Summary
Define and execute the multi-year enterprise data engineering roadmap aligned with business strategy, establishing standards and governance practices for data architecture, engineering, and platform operations. Own data engineering budgets, cloud spend optimization, and vendor relationships while driving modernization initiatives including cloud migration, real-time analytics, and AI/ML enablement. Lead multiple engineering team members, develop succession plans, and manage agile ceremonies to maintain alignment and productivity. Partner with product managers, enterprise teams, and technical stakeholders to standardize data products and ensure compliance with security and regulatory requirements. Conduct rigorous unit testing and peer reviews to ensure high-quality, scalable code. Report directly to the Sr Director of Data Engineering with occasional travel for stakeholder engagement.
Required Qualifications
- Minimum of 10 years of experience in Data Engineering or equivalent, demonstrated through work experience, academic training, military service, or education
- At least 5 years of proven management experience, showcasing the ability to lead and develop high-performing teams
- A minimum of 5 years of hands-on experience in data warehousing, specifically utilizing Snowflake
- Comprehensive understanding of systems architecture and design principles to effectively develop and implement data solutions
- Adept at building in-depth subject matter knowledge in individual data domains, with the capacity to guide and mentor development teams
- Proficient in development languages such as Python, SQL, Scala, or Java
- Experienced in real-time data and streaming application development, with at least 2 years of direct exposure
- Demonstrated experience with at least one public cloud platform, such as AWS, Microsoft Azure, or Google Cloud, for a minimum of 3 years
- Familiarity with data ecosystem tools for real-time batch data ingestion, ETL processing, and reporting
- Background in the supply chain or distribution industry, providing valuable insights and domain-specific strategies
- Exposure to multiple platform stacks and tools including but not limited to Databricks, Matillion, DBT, and Airflow Orchestration
- Experience in cloud data engineering and migration processes, enhancing organizational data capabilities
- Strong ability to collaborate with digital product managers and various stakeholders to deliver robust, cloud-based data solutions
- Proven experience in gathering technical and business requirements and effectively communicating them to internal and external partners
- Ability to manage and influence internal partners associated with the data technology function to achieve strategic objectives
- Experience in identifying opportunities for data engineering process improvements and developing risk control measures
- Proficient in managing and supporting risks encountered by the engineering team and driving continuous improvement efforts
- Bachelor's degree in Computer Science, Information Technology, or a related technical field from an accredited institution
- Minimum of 8 years of data engineering experience or its equivalent, which can be demonstrated through any combination of work experience, training, military service, or education
- At least 3 years of management experience
- At least 3 years in data warehousing, specifically with Snowflake
- Minimum of 10 years of experience in Data Engineering or equivalent, demonstrated through work experience, academic training, military service, or education
- At least 5 years of proven management experience, showcasing the ability to lead and develop high-performing teams
- A minimum of 5 years of hands-on experience in data warehousing, specifically utilizing Snowflake
- Comprehensive understanding of systems architecture and design principles to effectively develop and implement data solutions
- Adept at building in-depth subject matter knowledge in individual data domains, with the capacity to guide and mentor development teams
- Proficient in development languages such as Python, SQL, Scala, or Java
- Experienced in real-time data and streaming application development, with at least 2 years of direct exposure
- Demonstrated experience with at least one public cloud platform, such as AWS, Microsoft Azure, or Google Cloud, for a minimum of 3 years
- Familiarity with data ecosystem tools for real-time batch data ingestion, ETL processing, and reporting
- Background in the supply chain or distribution industry, providing valuable insights and domain-specific strategies
- Exposure to multiple platform stacks and tools including but not limited to Databricks, Matillion, DBT, and Airflow Orchestration
- Experience in cloud data engineering and migration processes, enhancing organizational data capabilities
- Strong ability to collaborate with digital product managers and various stakeholders to deliver robust, cloud-based data solutions
- Proven experience in gathering technical and business requirements and effectively communicating them to internal and external partners
- Ability to manage and influence internal partners associated with the data technology function to achieve strategic objectives
- Experience in identifying opportunities for data engineering process improvements and developing risk control measures
- Proficient in managing and supporting risks encountered by the engineering team and driving continuous improvement efforts
- Bachelor's degree in Computer Science, Information Technology, or a related technical field from an accredited institution
- Minimum of 8 years of data engineering experience or its equivalent, which can be demonstrated through any combination of work experience, training, military service, or education
- At least 3 years of management experience
- At least 3 years in data warehousing, specifically with Snowflake
- Must possess a minimum of 8 years of data engineering experience or its equivalent, which can be demonstrated through any combination of work experience, training, military service, or education
- Applicants are required to have accumulated at least 3 years of management experience and 3 years in data warehousing, specifically with Snowflake
- Demonstrates proficiency in data engineering principles and technologies, including cloud-based platforms such as AWS, Azure, or Google Cloud
- Proven track record in developing data solutions, data warehousing (e.g., Snowflake), and familiarity with multiple platform stacks and tools (e.g., Databricks, Matillion)
- Exhibits strong leadership capabilities by guiding and mentoring engineering teams
- Manages resource allocation and oversees agile ceremonies, including daily scrums, backlog grooming, sprint planning, and retrospectives
Desired Qualifications
- Advanced experience in development using modern programming languages such as Python, SQL, Scala, or Java, with a minimum of 5 years leading development projects in these or similar languages
- Demonstrated proficiency in working with real-time data processing and streaming applications, with at least 2 years of hands-on experience in this area
- Extensive experience, over a minimum of 3 years, in leveraging public cloud services, such as AWS, Microsoft Azure, or Google Cloud, to architect and deploy scalable data solutions
- Familiarity with supply chain or distribution industry practices, which would facilitate a deeper understanding of the SRS Distribution business model and objectives
- Competency in handling and integrating multiple platform stacks and tools, such as Databricks, Matillion, DBT, and Airflow Orchestration, to enhance data processing workflows
- Proven expertise in conceptualizing and designing systems architecture specifically tailored for data-centric solutions
- Experience with data ecosystem tools, emphasizing real-time batch data ingestion, ETL processes, and effective reporting solutions
- A strong background in cloud data engineering and a history of successful data migrations, underscoring the ability to transition legacy systems into modern cloud-based architectures
- Prior experience in technical roles within the distribution industry, with a focus on optimizing data management processes and systems
- Demonstrated ability to lead technical teams, with a focus on promoting best practices in data modeling and establishing governance standards across the data environment
- Strong business acumen with proven experience in translating complex business requirements into scalable and effective technical solutions, fostering cross-functional collaboration and alignment
- Master's degree in Computer Science, Data Engineering, Information Technology, or a related technical field
- Certified Data Management Professional (CDMP)
- AWS Certified Data Analytics Specialty
- Google Professional Data Engineer Certification
- Microsoft Certified: Azure Data Engineer Associate
- Snowflake SnowPro Core Certification
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